LAUSR

To improve the fusion quality of infrared and visible images and highlight target and scene details, in this paper, a novel infrared and visible image fusion algorithm is proposed. First, a method for combining dynamic range compression and contrast restoration based on a guided filter is adopted to enhance the contrast of visible source images. Second, guided filter-based image multiscale decomposition is used to decompose images into base layers and detail layers. For base layer fusion, a fusion strategy based on the detail and energy measurements of the source image is proposed to determine the pixel value of the fused image base layer such that the energy loss of the fusion can be reduced and the texture detail features are highlighted to obtain more source image details. Finally, recursive separation and weighted histogram equalization methods are applied to optimize the fused image. Experimental results show that the fusion algorithm and fusion strategy proposed in this paper can effectively improve fusion image clarity, while more detailed target and scene information can still be retained.